docs: def _get_Berger_data(verbose=True):
      '''Read in the Berger and Loutre orbital table as a pandas dataframe, convert to xarray
      '''
      # The first column of the data file is used as the row index, and represents kyr from present
      orbit91_pd, path = load_data_source(local_path = local_path,
                      remote_source_list = [threddspath, NCDCpath],
                      open_method = pd.read_csv,
                      open_method_kwargs = {'delim_whitespace': True, 'skiprows':1},
                      verbose=verbose,)
      #  As xarray structure with the dimension named 'kyear'
      orbit = xr.Dataset(orbit91_pd).rename({'dim_0': 'kyear'})
      #  Now change names
      orbit = orbit.rename({'ECC': 'ecc', 'OMEGA': 'long_peri',
                            'OBL': 'obliquity', 'PREC': 'precession'})
      # add 180 degrees to long_peri (see lambda definition, Berger 1978 Appendix)
      orbit['long_peri'] += 180.
      orbit['precession'] *= -1.
  
      orbit.attrs['Description'] = 'The Berger and Loutre (1991) orbital data table'
      orbit.attrs['Citation'] = 'https://doi.org/10.1016/0277-3791(91)90033-Q'
      orbit.attrs['Source'] = path
      orbit.attrs['Note'] = 'Longitude of perihelion is defined to be 0 degrees at Northern Vernal Equinox. This differs by 180 degrees from orbit91 source file.'
      return orbit